Discovering diverse association rules from multidimensional schema

Highlights：

• We propose a knowledge discovery methodology to discover diverse association rules.

• We utilize machine learning and statistical techniques for designing schema.

• We identify and rank the most informative dimensions present high dimensional schema.

• We extract informative data cubes at different levels of data abstraction.

• We perform case studies on three real-world datasets to validate our methodology.